>"Your analysis tells nothing about whether the model of fair coin being flipped is confirmed. You see a deviation of 0.06 in the mean and 0.47 in the variance.

>"Your analysis tells nothing about whether the model of fair coin being flipped is confirmed. You see a deviation of 0.06 in the mean and 0.47 in the variance. Is that negligible?" Th easiest way is to just run a simulation thousands or millions of times then check how often the observed results occurred. Eg, using R again to get distributions for the mean and sd for the model and getting the one sided p-value: p = 0.5 nDays = 365 nPerDay = 20 obs = rbinom(nDays, nPerDay, p) sim = replicate(1e3, rbinom(nDays, nPerDay, p)) stats = apply(dat, 2, function(x) c(mean(x), var(x))) mean(stats[1,] > mean(obs)) mean(stats[2,] > var(obs)) >"In the frequentist framework, there is no way to confirm a model. The only way to arrive at a model is to falsify all “simpler” models one can think of, that might possibly have explained the data." That isn't frequestist. Its the so-called "NHST hybrid" which it seems confused stats 101 authors in the 1930-1940s cobbled together from the ideas of Ronald Fisher, Jerzy Neyman, and Egon Pearson. This is a decent intro to that topic, but there are thousands of papers on this: http://library.mpib-berlin.mpg.de/ft/gg/GG_Mindless_2004.pdf http://library.mpib-berlin.mpg.de/ft/gg/GG_Mindless_2004.pdf